• 대한원격탐사학회지
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• 제27권6호
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• pp.703-715
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• 2011

Forests have been considered one of the most important ecosystems on the earth, affecting the lives and environment. The sustainable forest management requires accurate and timely information of forest and tree parameters. Appropriately interpreted remotely sensed imagery can provide quantitative data for deriving forest information temporally and spatially. Especially, analysis of individual tree detection and crown delineation is significant issue, because individual trees are basic units for forest management. Individual trees in aerial imagery have reflectance characteristics according to tree species, crown shape and hierarchical status. This study suggested a method that identified individual trees and delineated crown boundaries through adopting gradient method algorithm to amplified greenness data using red and green band of aerial imagery. The amplification of specific band value improved possibility of detecting individual trees, and gradient method algorithm was performed to apply to identify individual tree tops. Additionally, tree crown boundaries were explored using spectral intensity pattern created by geometric characteristic of tree crown shape. Finally, accuracy of result derived from this method was evaluated by comparing with the reference data about individual tree location, number and crown boundary acquired by visual interpretation. The accuracy ($\hat{K}$) of suggested method to identify individual trees was 0.89 and adequate window size for delineating crown boundaries was $19{\times}19$ window size (maximum crown size: 9.4m) with accuracy ($\hat{K}$) at 0.80.

• 정보처리학회논문지D
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• 제8D권5호
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• pp.507-512
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• 2001

특징 기반 유사성은 멀티미디어 데이터베이스 시스템에서 중요한 연구 쟁점이 되고 있다. 멀티미디어 데이터의 특징이 멀티미디어 객체들을 구별하는데 유용하다지만 특징 벡터의 차원의 수가 증가함에 따라 종래의 다차원 데이터 구조의 성능은 떨어지는 경향이 있다. $R^{*}-Tree$는 R-Tree의 가장 성공적인 병형으로 본 논문에서 고차원 특징 벡터를 위한 새로운 인덱싱 방법으로서 자기 조직화 맵 기반 $R^{*}-Tree$를 제안한다. 자기 조직화 맵 기잔 $R^{*}-Tree$는 고차원 데이터를 좀더 스칼라화해서 탐색할 수 있도록 SOM과 $R^{*}-Tree$를 결합하여 구축한 인덱싱 기법이다. 자기 조직 맵은 고차원 특징 벡터들로부터 2차원 공간으로의 맵핑을 제공한다. 그러나 맵을 위상 특징 맵이라 하고 인접 노느에서 서로 유사한 특징 벡터들을 모아서 입력데이터의 특징 공간들 속에 유사성을 보존하는데 위상 특징 맵의 각 노드는 코드북 벡터를 가지고 있다. 실험적으로 4만개의 이미지로부터 추출된 색깔 특징 벡터들을 이용하여 자기 조직화 맵 기반 $R^{*}-Tree$의 검색시간 비용과 자기 조직화 맵과 $R^{*}-Tree$의 검색 시간 비용을 비교한다. 그 결과 $R^{*}-Tree$를 구축하는데 필요한 노드 수와 검색 시간 비용이 감소됨으로써 자기 조직화 맵 기반 $R^{*}-Tree$는 자기 조직화 맵과 $R^{*}-Tree$보다 훨씬 우수한 성능을 나타냄이 입증되었다.

• 한국통신학회논문지
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• 제37권5A호
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• pp.358-366
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• 2012

LED-ID (Light Emitting Diode - Identification) is one of the key technologies for identification, data transmission, and illumination simultaneously. This is the new paradigm in the identification technology environment. There are many issues are still now challenging to achieve high performance in LED-ID system. Collision issue is one of them. Actually this is the most significant issue in all identification system. LED-ID system also suffers from collision problem. In our system, collision occurs when two or more readers transmit data to tag at the same time or vice versa. There are many anti-collision protocols to resolve this problem; such as: Slotted ALOHA, Basic Frame Slotted ALOHA, Query Tree, Tree Splitting, and Q-Algorithm etc. In this paper, we propose modified Q-Algorithm to resolve collision at tag. The proposed protocol is based on Q-Algorithm and used the information of arrived readers to a tag from neighbor. The information includes transmitting slot number of readers and the number of readers that can be arrived in next slot. Our proposed protocol can reduce the numbers of collision slot and the successful time to identify all readers. In this paper our simulation and theoretical results are presented.

• 대한안전경영과학회지
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• 제6권2호
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• pp.211-229
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• 2004

The basis of cyber trading has been sufficiently developed with innovative advancement of Internet Technology and the tendency of stock market investment has changed from long-term investment, which estimates the value of enterprises, to short-term investment, which focuses on getting short-term stock trading margin. Hence, this research shows a Short-term Stock Price Forecasting System on Learning Agent System using DTA(Decision Tree Algorithm) ; it collects real-time information of interest and favorite issues using Agent Technology through the Internet, and forms a decision tree, and creates a Rule-Base Database. Through this procedure the Short-term Stock Price Forecasting System provides customers with the prediction of the fluctuation of stock prices for each issue in near future and a point of sales and purchases. A Human being has the limitation of analytic ability and so through taking a look into and analyzing the fluctuation of stock prices, the Agent enables man to trace out the external factors of fluctuation of stock market on real-time. Therefore, we can check out the ups and downs of several issues at the same time and figure out the relationship and interrelation among many issues using the Agent. The SPFA (Stock Price Forecasting System) has such basic four phases as Data Collection, Data Processing, Learning, and Forecasting and Feedback.

• 디지털산업정보학회논문지
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• 제14권1호
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• pp.27-34
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• 2018

Various messages generated in vehicles are transmitted based on the wireless telecommunication which is a core technology of vehicle to everything (V2X). However, the hackers attack them upon penetration to the system and network to cause the generation of users' inconveniences for vehicular communication. Moreover, huge damage could be occurred in terms of physical and materialistic areas if the users in the vehicles were attacked in the communication environment. Therefore, this study was to design the safe communication protocol using hash tree technique in the V2X environments. Using hash tree technique, processes of issuing certificate and registration and communication protocol were designed, and safety analysis was performed on the attacking technique which is occurred in the existing vehicles. Approximately 62% of decrease in the capacity analysis was found upon comparative analysis of telecommunication processes with the system to issue the certificate which is used in the existing vehicles.

• International journal of advanced smart convergence
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• 제12권1호
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• pp.92-100
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• 2023

Wireless communication technology is becoming increasingly prevalent in smart factories, but the rise in the number of wireless devices can lead to interference in the ISM band and obstacles like metal blocks within the factory can weaken communication signals, creating radio shadow areas that impede information exchange. Consequently, accurately determining the radio communication coverage range is crucial. To address this issue, a Radio Environment Map (REM) can be used to provide information about the radio environment in a specific area. In this paper, a technique for estimating an indoor REM usinga mobile robot and machine learning methods is introduced. The mobile robot first collects and processes data, including the Received Signal Strength Indicator (RSSI) and location estimation. This data is then used to implement the REM through machine learning regression algorithms such as Extra Tree Regressor, Random Forest Regressor, and Decision Tree Regressor. Furthermore, the numerical and visual performance of REM for each model can be assessed in terms of R2 and Root Mean Square Error (RMSE).

• Nuclear Engineering and Technology
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• 제56권1호
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• pp.141-146
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• 2024

Station blackout (SBO) risk is one of the most significant contributors to nuclear power plant risk. In this paper, the sequence probability formulas derived by the convolution approach are compared with those derived by the conventional event tree/fault tree (ET/FT) approach for the SBO situation in which emergency diesel generators fail to start. The comparison identifies what makes the ET/FT approach more conservative and raises the issue regarding the mission time of a turbine-driven auxiliary feedwater pump (TDP), which suggests a possible modeling improvement in the ET/FT approach. Monte Carlo simulations with up-to-date component reliability data validate the convolution approach. The sequence probability of an alternative alternating current diesel generator (AAC DG) failing to start and the TDP failing to operate owing to battery depletion contributes most to the SBO risk. The probability overestimation of the scenario in which the AAC DG fails to run and the TDP fails to operate owing to battery depletion contributes most to the SBO risk overestimation determined by the ET/FT approach. The modification of the TDP mission time renders the sequence probabilities determined by the ET/FT approach more consistent with those determined by the convolution approach.

• 정보처리학회논문지C
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• 제11C권6호
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• pp.851-862
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• 2004

RFID(Radio Frequency IDentification) 기술은 RF 신호를 사용하여 물품에 부착된 전자태그를 식별하는 비접촉 기술이다. 식별 영역 내에 다수의 태그가 존재한 경우에 요구되는 다중 태그 식별 문제는 RFID 기술 중에서도 핵심 이슈이며 이 문제는 충돌방지 알고리즘을 통하여 해결할 수 있다. 하지만 기존 알고리즘들은 구현의 복잡성과 낮은 성능이 문제로 제기되고 있다. 본 논문에서는 이러한 문제를 해결할 수 있는 트리 기반 메모리래스 충돌방지 알고리즘인 충돌 추적(Collision Tracking) 트리 알고리즘을 제안하고 성능평가 결과를 제시한다. 성능평가 결과 제안하는 알고리즘이 초당 749개의 태그를 식별하면서 기존 트리 기반 메모리래스 알고리즘인 트리-워킹 알고리즘과 쿼리 트리 알고리즘에 비해 각각 약 49배와 2.4배의 성능향상을 확인할 수 있었다.

• 한국조경학회지
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• 제25권1호
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• pp.47-61
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• 1997

This study was conducted to grasp the present condition of the name and the related text of the domestic laws (97 statutes, 1 examination, 1 guide, 3 ordinances, 1 leading case) in force which were connected with landscape plant and planting. Examining the general tree-planting system of America, the related foreign laws(1 constitution, 44 statutes, 31 ordinances, 6 leading cases) were arranged in the name and the text and classified by nations of regional groups and it was considered to the mutual relation with lots of laws which are scattered with the various laws. To examine the points at issue of the related domestic laws and to study the related foreign laws, the remedies for the domestic laws being at issue were proposed. That is : A change of the landscape planting concept, the introduction of the landscape planting cost compared with the total construction cost, the unification of the landscape planting ordinances as the unit of city, the clarification of the completion period for the depect of the replaced trees. putting the conservation and production of the top soil under an obligation the adoption of a licence system for the tree planting within the river area, the introduction of the allotment system for landscape architectural expenses, the encouragement of making a hedge, the settlement for the problems of the trees loss compensation, the necessity for the quality test to the landscape planting works, the intensification of the punitive rules to the illegal felling and planting of the trees in the greenzone area, the application of the Labor Standard Act to the landscape planting laborers. The laws relating to landscape plant and planting are prescribed dispersedly in the many other related laws and it is concluded to be impossible for the legislation of the singular law which is applied uniformly to the department of the tree-planting. Hereafter it should be required to analyze concretely in detail the each text of the related laws by means of the joint studies between the professional landscape architects and the lawyers.

• 경영정보학연구
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• 제22권4호
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• pp.41-58
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• 2020

본 연구는 한국고용정보원 공공디비 자료에 의사결정나무 기법을 적용하여 근로자들이 이직을 하려고 하는 요인을 분석하고자 한다. 이를 통하여 근로자들의 고용유지 강화방안을 제시한다. 분석대상은 근속기간이 4개월 이상으로 수습 기간이 지난 정규직 근로자를 대상으로 하였고, 분석목표는 해당 근로자들의 이직준비 여부에 영향을 주는 의사결정 규칙을 도출하는 것으로 하였다. 타겟 분석 데이터는 한국고용정보원에서 발간된 수집한 「2017년 대졸자 직업이동경로조사」를 사용하였다. 분석결과 '교육수준과 일의 수준의 일치 정도', '개인 발전 가능성', '직무 관련 교육 및 훈련', '승진 제도', '임금 및 소득', '일자리에 대한 사회적 평판', '고용 안정성' 등이 이직준비 여부에 영향을 주는 주요요인으로 나타났다.